Abstract
Language recognition is the way by which the language of a digital speech utterance is recognized automatically by a computer. Commenced Language Identification Systems sequentially transform the speech signal into discrete units, and then apply statistical methods on the resultant units to extract their language information. Today, a large number of audio retrieval features exists for automatic speech and language recognition. The proposed method has nominated an automatic system for well-known multi-languages. The identification has been done using a new set of audio features. The suitable feature has been adopted. This includes Zero-Crossing Rate, Spectral Flux, Pitch, Mel-frequency Cepstral Coefficients, Tempo, and Short-Time Energy. These features have been used exclusively for identifying the language along with the help of classifiers and feature selection algorithms.
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This chapter does not contain any studies with human participants or animals performed by any of the authors.
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Agarwal, S., Chatterjee, A., Yasmin, G. (2020). Automatic Multilingual System from Speech. In: Das, A., Nayak, J., Naik, B., Pati, S., Pelusi, D. (eds) Computational Intelligence in Pattern Recognition. Advances in Intelligent Systems and Computing, vol 999. Springer, Singapore. https://doi.org/10.1007/978-981-13-9042-5_13
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DOI: https://doi.org/10.1007/978-981-13-9042-5_13
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